Entertainment device safety system and related methods of use

ABSTRACT

An entertainment device safety system includes a video camera configured to capture video of an entertainment device and a user of the entertainment device and a video analytic module to perform real-time video processing of the captured video to generate non-video data from video. A computer receives the video and the non-video data from the video camera analyzes the video or the non-video data to determine a user position in relation to the entertainment device. The user position is compared to a user position rule to determine whether the user position violates the user position rule. A notification is transmitted in response to a determination that the user position violates the user position rule.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of U.S. patentapplication Ser. No. 14/542,013, filed on Nov. 14, 2014, now U.S. Pat.No. 9,773,163, which claims priority to, and the benefit of, U.S.Provisional Application Ser. No. 61/904,201, filed on Nov. 14, 2013, thedisclosures of which are herein incorporated by reference in theirentirety.

BACKGROUND

1. Technical Field

The present disclosure relates to video observation systems and methodsof use, and in particular, to a real-time video safety system fordetecting unsafe conditions, non-conformities, and/or violations ofamusement park safety rules.

2. Background of Related Art

Companies are continually trying to identify specific user behavior inorder to improve throughput, efficiency and, in some instances, minimizethe safety risk to its consumers or in the service industry, the users.One particular industry that places a high regard on consumer or usersafety is the entertainment industry, and, in particular, amusement ortheme parks which provide rides or include user participation of somesort.

Amusement parks are typically required to provide some measure of usersafety in the form of mechanical or electromechanical latches, pins,harnesses, gates, belts, and the like which are typically manuallyoperated by the user, or automatically engaged after the user isproperly positioned on the ride. In some instances, a ride attendant isresponsible for checking or verifying that the safety feature isproperly engaged before the ride commences. In some more advanced rides,some sort of electromechanical feedback may be employed to verify thatthe safety feature is properly engaged. Relying on a ride attendant hasobvious drawbacks in terms of safety issues and therefore, anelectromechanical safety feature may reduce human error in certainsituations.

Surveillance systems and the like are widely used in various industries.In certain instances, one or more video cameras continually stream videoto a video recorder. Typically, a video recorder may include acomputer-based server which can record multiple simultaneous videostreams to a memory, such as a hard disk or solid state memory. A bufferperiod of 8, 12, 24, or 48 hours, for example, may be use used. In manyinstances, no need will arise to review or store the recorded video sothe buffer is overwritten. In other systems, a longer period of time maybe utilized or the buffer is weeks or months of data being stored andsaved for particular purposes. When an event occurs, the video isavailable for review, archiving, and analysis of the video data. Onoccasion, police, rescue personal, or other authorities may need toreview the various camera systems in a particular area or arena forpurposes necessary to their investigation.

There exists a need to develop an analytical technology that providesreal time safety features to prevent consumer or user injury in case ofhuman error.

SUMMARY

The following definitions are applicable throughout this disclosure:

A “video camera” may refer to an apparatus for visual recording.Examples of a video camera may include one or more of the following: avideo imager and lens apparatus; a video camera; a digital video camera;a color camera; a monochrome camera; a camcorder; a PC camera; a webcam;an infrared (IR) video camera; a low-light video camera; a thermal videocamera; a closed-circuit television (CCTV) camera; a pan/tilt/zoom (PTZ)camera; a hemispherical or fisheye camera, and a video sensing device. Avideo camera may be positioned to perform observation of an area ofinterest.

“Video” may refer to the motion pictures obtained from a video camerarepresented in analog and/or digital form. Examples of video mayinclude: television; a movie; an image sequence from a video camera orother observer; an image sequence from a live feed; a computer-generatedimage sequence; an image sequence from a computer graphics engine; animage sequence from a storage device, such as a computer-readablemedium, a digital video disk (DVD), or a high-definition disk (HDD); animage sequence from an IEEE 1394-based interface; an image sequence froma video digitizer; or an image sequence from a network.

“Video data” is a visual portion of the video.

“Non-video data” is non visual information extracted from the videodata, and may include metadata associated with the video data.

A “video sequence” may refer to a selected portion of the video dataand/or the non-video data.

“Video processing” may refer to any manipulation and/or analysis ofvideo data, including, for example, compression, editing, and performingan algorithm that generates non-video data from the video.

A “frame” may refer to a particular image or other discrete unit withinvideo.

A “computer” may refer to one or more apparatus and/or one or moresystems that are capable of accepting a structured input, processing thestructured input according to prescribed rules, and producing results ofthe processing as output. Examples of a computer may include: astationary and/or portable computer; a computer having a singleprocessor, multiple processors, or multi-core processors, which mayoperate in parallel and/or not in parallel; a general purpose computer;a supercomputer; a mainframe; a super mini-computer; a mini-computer; aworkstation; a micro-computer; a server; an interactive television; aweb appliance; a telecommunications device with internet access; ahybrid combination of a computer and an interactive television; aportable computer; a tablet personal computer (PC); a personal digitalassistant (PDA); a portable telephone; application-specific hardware toemulate a computer and/or software, such as, for example, a digitalsignal processor (DSP), a field-programmable gate array (FPGA), anapplication specific integrated circuit (ASIC), an application specificinstruction-set processor (ASIP), a chip, chips, or a chip set; a systemon a chip (SoC), or a multiprocessor system-on-chip (MPSoC); an opticalcomputer; a quantum computer; a biological computer; a nanotubecomputer; and any apparatus that may accept data, may process data inaccordance with one or more stored software programs, may generateresults, and typically may include input, output, storage, arithmetic,logic, and control units.

“Software” may refer to prescribed rules to operate a computer. Examplesof software may include: code segments; instructions; applets;pre-compiled code; compiled code; interpreted code; computer programs;and programmed logic.

A “computer-readable medium” may refer to any storage device used forstoring data accessible by a computer. Examples of a computer-readablemedium may include: a magnetic hard disk; a floppy disk; an opticaldisk, such as a CD-ROM and a DVD; a magnetic tape; a flash removablememory; a memory chip; and/or other types of media that may storemachine-readable instructions thereon.

A “computer system” may refer to a system having one or more computers,where each computer may include a computer-readable medium embodyingsoftware to operate the computer. Examples of a computer system mayinclude: a distributed computer system for processing information viacomputer systems linked by a network; two or more computer systemsconnected together via a network for transmitting and/or receivinginformation between the computer systems; and one or more apparatusesand/or one or more systems that may accept data, may process data inaccordance with one or more stored software programs, may generateresults, and typically may include input, output, storage, arithmetic,logic, and control units.

A “network” may refer to a number of computers and associated devicesthat may be connected by communication facilities. A network may involvepermanent connections such as cables or temporary connections such asthose made through telephone or other communication links. A network mayfurther include hard-wired connections (e.g., coaxial cable, twistedpair, optical fiber, waveguides, etc.) and/or wireless connections(e.g., radio frequency waveforms, free-space optical waveforms, acousticwaveforms, etc.). Examples of a network may include: an internet, suchas the Internet; an intranet; a local area network (LAN); a wide areanetwork (WAN); and a combination of networks, such as an internet and anintranet. Exemplary networks may operate with any of a number ofprotocols, such as Internet protocol (IP), asynchronous transfer mode(ATM), and/or synchronous optical network (SONET), user datagramprotocol (UDP), IEEE 802.x, etc.

“Real time” analysis or analytics means processing real time or “live”video and providing near instantaneous reports or warnings of abnormalconditions (pre-programmed conditions), abnormal scenarios (loitering,convergence, separation of clothing articles or backpacks, briefcases,groceries for abnormal time, etc or other scenarios based on behavior ofelements (customers, patrons, people in crowd, etc.) in one or multiplevideo streams.

“Post time” analysis or analytics means processing stored or saved orvideo from a camera source (from a particular camera system (store,parking lot, street) or other video data (cell phone, home movie, etc.))and providing reports or warnings of abnormal conditions(post-programmed conditions), abnormal scenarios (loitering,convergence, separation of clothing articles or backpacks, briefcases,groceries for abnormal time, etc., and/or other scenarios based onbehavior of elements (customers, patrons, people in crowd, etc.) in astored one or more video streams.

“Video Tripwire” means the detection of objects moving in one or morespecified direction(s) crossing over a line defined within the camera'sview.

“Video TripBox” means the detection of objects entering into, and/orexiting from, a closed boundary such as a polygon defined within thecamera's view.

In an aspect, the present disclosure is directed to an entertainmentdevice safety system. The disclosed system includes a video cameraconfigured to capture video of an entertainment device and a user of theentertainment device and a video analytic module to perform real-timevideo processing of the captured video to generate non-video data fromthe captured video. The disclosed system further includes a computerconfigured to receive the video and the non-video data from the videocamera, wherein the computer is programmed to analyze one of the videoand the non-video data to determine a user position in relation to theentertainment device, compare the user position to a user position rule,determine whether the user position violates the user position rule, andtransmit a notification in response to a determination that the userposition violates the user position rule.

In some embodiments, the computer is further programmed to perform thesteps of analyzing one of the video and the non-video data to determinethe entertainment device type and choosing the user position rule basedat least in part upon the entertainment device type.

In some embodiments, the computer is further programmed to perform thesteps of analyzing one of the video and the non-video data to determinea safety device position in relation to the entertainment device,comparing the safety device position to a safety device position rule,determining whether the safety device position violates the safetydevice position rule, and transmitting a notification in response to adetermination that safety device position violates the safety deviceposition rule.

In some embodiments, the computer is further programmed to perform thesteps of analyzing the video or the non-video data to determine theentertainment device type and choosing the safety device position rulebased at least in part upon the entertainment device type.

In some embodiments, the computer is further programmed to perform thestep of choosing the safety device position rule based at least in partupon the entertainment device type.

In some embodiments, the safety device position rule is based at leastin part upon a safety device color.

In some embodiments, the video camera is configured to capture infra-redimages and the safety device includes an fluorescent infra-red pigment.In some embodiments, the system includes a source of infrared light.

In some embodiments, the user position rule includes at least one of anaspect ratio, an absolute height, an absolute width, and a weightedcentroid.

In some embodiments, the computer is further configured to receive aposition signal from the entertainment device.

In some embodiments, transmitting a notification includes causing theentertainment device to cease operation. In some embodiments,transmitting a notification includes activating a visual indicatoradjacent to the user.

In another aspect, the present disclosure is directed to anentertainment device safety method. The disclosed method includescapturing video of an entertainment device and a user of theentertainment device and performing real-time video processing of thecaptured video to generate non-video data from the captured video. Thedisclosed method further includes analyzing one of the video and thenon-video data to determine a user position in relation to theentertainment device, comparing the user position to a user positionrule, determining whether the user position violates the user positionrule, and transmitting a notification in response to a determinationthat the user position violates the user position rule.

In some embodiments, the video or the non-video data is analyzed todetermine the entertainment device type and the user position rule ischosen based at least in part upon the entertainment device type.

In some embodiments, the video and the non-video data is analyzed todetermine a safety device position in relation to the entertainmentdevice, comparing the safety device position to a safety device positionrule, determining whether the safety device position violates the safetydevice position rule, and transmitting a notification in response to adetermination that safety device position violates the safety deviceposition rule.

In some embodiments, the video and the non-video data is analyzed todetermine the entertainment device type and the safety device positionrule is chosen based at least in part upon the entertainment devicetype.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a system block diagram of an embodiment of a videoobservation, surveillance and verification system in accordance with thepresent disclosure.

DETAILED DESCRIPTION

Particular embodiments of the present disclosure are describedhereinbelow with reference to the accompanying drawings; however, it isto be understood that the disclosed embodiments are merely examples ofthe disclosure, which may be embodied in various forms. Well-knownfunctions or constructions are not described in detail to avoidobscuring the present disclosure in unnecessary detail. Therefore,specific structural and functional details disclosed herein are not tobe interpreted as limiting, but merely as a basis for the claims and asa representative basis for teaching one skilled in the art to variouslyemploy the present disclosure in virtually any appropriately detailedstructure. In this description, as well as in the drawings,like-referenced numbers represent elements which may perform the same,similar, or equivalent functions.

Additionally, the present disclosure may be described herein in terms offunctional block components, code listings, optional selections, pagedisplays, and various processing steps. It should be appreciated thatsuch functional blocks may be realized by any number of hardware and/orsoftware components configured to perform the specified functions. Forexample, the present disclosure may employ various integrated circuitcomponents, e.g., memory elements, processing elements, logic elements,look-up tables, and the like, which may carry out a variety of functionsunder the control of one or more microprocessors or other controldevices.

Similarly, the software elements of the present disclosure may beimplemented with any programming or scripting language such as C, C++,C#, Java, COBOL, assembler, PERL, Python, PHP, or the like, with thevarious algorithms being implemented with any combination of datastructures, objects, processes, routines or other programming elements.The object code created may be executed on a variety of operatingsystems including, without limitation, Windows®, Macintosh OSX®, iOS®,linux, and/or Android®.

Further, it should be noted that the present disclosure may employ anynumber of conventional techniques for data transmission, signaling, dataprocessing, network control, and the like. It should be appreciated thatthe particular implementations shown and described herein areillustrative of the disclosure and its best mode and are not intended tootherwise limit the scope of the present disclosure in any way. Examplesare presented herein which may include sample data items (e.g., names,dates, etc.) which are intended as examples and are not to be construedas limiting. Indeed, for the sake of brevity, conventional datanetworking, application development and other functional aspects of thesystems (and components of the individual operating components of thesystems) may not be described in detail herein. Furthermore, theconnecting lines shown in the various figures contained herein areintended to represent example functional relationships and/or physicalor virtual couplings between the various elements. It should be notedthat many alternative or additional functional relationships or physicalor virtual connections may be present in a practical electronic datacommunications system.

As will be appreciated by one of ordinary skill in the art, the presentdisclosure may be embodied as a method, a data processing system, adevice for data processing, and/or a computer program product.Accordingly, the present disclosure may take the form of an entirelysoftware embodiment, an entirely hardware embodiment, or an embodimentcombining aspects of both software and hardware. Furthermore, thepresent disclosure may take the form of a computer program product on acomputer-readable storage medium having computer-readable program codemeans embodied in the storage medium. Any suitable computer-readablestorage medium may be utilized, including hard disks, CD-ROM, DVD-ROM,optical storage devices, magnetic storage devices, semiconductor storagedevices (e.g., USB thumb drives) and/or the like.

In the discussion contained herein, the terms “user interface element”and/or “button” are understood to be non-limiting, and include otheruser interface elements such as, without limitation, a hyperlink,clickable image, and the like.

The present disclosure is described below with reference to blockdiagrams and flowchart illustrations of methods, apparatus (e.g.,systems), and computer program products according to various aspects ofthe disclosure. It will be understood that each functional block of theblock diagrams and the flowchart illustrations, and combinations offunctional blocks in the block diagrams and flowchart illustrations,respectively, can be implemented by computer program instructions. Thesecomputer program instructions may be loaded onto a general purposecomputer, special purpose computer, mobile device or other programmabledata processing apparatus to produce a machine, such that theinstructions that execute on the computer or other programmable dataprocessing apparatus create means for implementing the functionsspecified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meansthat implement the function specified in the flowchart block or blocks.The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer-implemented process such that theinstructions that execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

Accordingly, functional blocks of the block diagrams and flowchartillustrations support combinations of means for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instruction means for performing the specified functions. Itwill also be understood that each functional block of the block diagramsand flowchart illustrations, and combinations of functional blocks inthe block diagrams and flowchart illustrations, can be implemented byeither special purpose hardware-based computer systems that perform thespecified functions or steps, or suitable combinations of specialpurpose hardware and computer instructions.

One skilled in the art will also appreciate that, for security reasons,any databases, systems, or components of the present disclosure mayconsist of any combination of databases or components at a singlelocation or at multiple locations, wherein each database or systemincludes any of various suitable security features, such as firewalls,access codes, encryption, de-encryption, compression, decompression,and/or the like.

The scope of the disclosure should be determined by the appended claimsand their legal equivalents, rather than by the examples given herein.For example, the steps recited in any method claims may be executed inany order and are not limited to the order presented in the claims.Moreover, no element is essential to the practice of the disclosureunless specifically described herein as “critical” or “essential.”

It is important to note that the present disclosure goes beyond facialrecognition software (which may be utilized in conjunction herewith) andprovides additional algorithms and analytics for tracking purposes asexplained below. In addition, it is not necessary in certain instancesthat facial recognition be utilized to flag or track someone orsomething and the presently described system may be employed withoutfacial recognition software or algorithms which may prove insensitive tocertain moral, federal or local laws.

The system may be able to combine pre-programmed analytics to alert forone or more (or a combination of) abnormal scenarios. For example, aperson getting out of his/her seat after the ride has commenced, aharness or safety bar coming unlatched after the ride has commenced, achild standing after the ride has commenced, a child climbing into aparent's lap after the ride has commenced, etc.

The present disclosure relates to a video analytical safety system thatanalyzes, in real time, certain safety conditions and notifies the rideoperators of a fault condition or automatically stops the ride dependingon the severity of the condition. As such, a video camera equipped withvideo analytics is positioned at various locations along the ride and isconfigured or programmed to recognize various unsafe conditions. Forexample, at the beginning of the ride, a ride operator is typicallyprovided with some sort of height aid that allows the ride operator toassess the height of a child or small adult prior to allowing the personaccess to the ride, e.g., a height bar. These height requirements areprovided by the ride manufacturers as a safety concern for persons thatfall below a certain height requirement. In some circumstances, smalladults or small children manipulate themselves onto the ride due toconfusion, lack of attention, or, in some cases, by bribing the rideattendant. As can be appreciated, this represents a safety concern forthe amusement park.

The present disclosure may alleviate these concerns by monitoring theheight bar with a video surveillance camera and analyzing each person'sheight as it relates to a particular ride. The level of sophisticationof the analytics can range from simple to very advanced. For example,the video system may simply be equipped to provide a “go” (green) or “nogo” (red) for each person stepping onto the ride. The level ofsophistication of the analytics can include a second or a series ofcameras that put a hold on the ride if that same person is allowed onthe ride. In other words, the system may recognize but not necessarilyidentify the person either facially or by some other set or group ofparameters which characterize that person for later analysis. In otherwords, in view of the sensitivities and legalities associated withfacial recognition and identification, and although the system may haveboth of these capabilities, the system may simply be configured torecognize a particular person based on facial characteristics or anycombination of other characteristics or individual features withoutcorrelating such features with an identification. Moreover, these videorecords of a particular person may be deleted on a daily basis toalleviate privacy concerns. In some embodiments, facial features of theindividual may be obscured by, for example, overlaying a blur or mosaiceffect to the individual's face.

Examples, of individualizing features which may be combined toindividualize a person: height, eye color, hair color, facial hair,clothing parameters (shirt color/type, plus hat color/type/orientation,plus pant color/type), other clothing items, e.g., watch, belt, jewelry,tattoos, etc. Any combination of these parameters can make an individualvideo record that may be compared or tracked for additional analysis.For example, once the record is made and the person is identified,another analytical camera for that same ride may be programmed toidentify the person and provide the ride operator with a defaultcondition and not start the ride. In more detail, embodiments of acamera or video system in accordance with the present disclosure areprogrammed to identify whether a subject individual meets the heightrequirements for a given ride. This determination may be made at a pointin the ride queue, at a height aid at the head of the queue, or at anysuitable point prior to a subject gaining entrance to the ride. In theevent the subject does not meet the height requirement, a visual profileof the individualizing features of the subject is stored, and flagged asineligible for the ride. A second camera is positioned beyond the rideentrance, for example, trained upon individuals walking along an innerhallway, at a staging area, or at individuals as positioned in or on theride. If the second camera detects, beyond the ride admission point, anindividual who did not meet the height requirements, an exceptioncondition is raised which may trigger any number of responses. Forexample, an operator or supervisor may be presented with a video feedshowing the ineligible individual highlighted among the other persons inthe frame, a visual indicator may be activated at the seat or positionat which the ineligible individual is located to quickly draw attentionto the situation, departure of the offending individual's ride may beprevented, a security record memorializing the facts of the event may bestored in a database, and so forth.

Moreover, the same video record may be sent to similar rides of the sameheight or greater to deny the person access to that ride. Once the videorecord is created, all the rides and the corresponding videosurveillance network for each ride (or the entire park) may be notifiedof the video record which further eliminates human error or other moreillicit human circumvention. In embodiments, this system can be mademore consumer-friendly by providing a camera at the beginning the lineor ride entry that flags the person as too small to go onto the ride(based on the video analytics of that ride or based on the networkrecognizing the person from being denied on another ride).

In some instances, it may prove advantageous for the amusement park toreadily identify or identify in real time the consumer or user that isflagged by the video record and automatically provide a selection ofalternate rides for that person based on size requirements. The ridesmay be arranged based on where the flagged person is located in thepark. In addition or alternatively, a flagged user may be identified tothe overall park video surveillance network and given a selection ofalternate rides. Once selected, the user may be placed in a fast lane(e.g., Disney's FASTPASS™) for that particular ride as a courtesy sincethe user may have already waited on a line for some time and was flaggedas ineligible for that ride.

The present disclosure may be utilized to alleviate other safetyconcerns which may be subject to human or mechanical error. For example,the video analytical system may be utilized as a secondary safetyfeature for all rides and tied into an emergency shut off for that ride.As can be appreciated, this type of system may also range very simple tosophisticated. For example, in the case of a malfunctioning safety bar(not engaged or raised at the commencement of the ride), the videoanalytical system may include a trip wire that automatically recognizesthe raised bar and shuts the ride until the bar is lowered or fixed.More complicated systems may detect or recognize (as described above) anunauthorized rider based on height (or some other characteristic thatmay be manually entered, e.g., a rowdy rider that was manually flagged).

The system may be configured to recognize a real time event aftercommencement of the ride, e.g., a person standing up, a child beingplace on a lap or escaping his/her harness or safety bar, a personreaching outside the ride. Any of these conditions may be automaticallydetected and the ride stopped (or slowed) to address these issues. Videoanalytics may be utilized for this purpose and may include video tripwires, or video trip boxes. The video analytics may be configured todetect features in a series of successive frames and/or may beconfigured to detect features in a single captured frame. For example, avideo camera may be configured to capture a section of roller coastertrack, from a point of view facing the front of the cars, above thetrack, such that a clear view of each passenger position of each car isobtained. When a car passes into the frame, an analysis of the video istriggered. The determination that a car has entered the frame may beaccomplished by image recognition (e.g., by an algorithmic comparisonbetween a frame of an empty track and a frame showing a car), by asensor on the track, via a signal received from a ride controller,and/or combinations thereof. The system may be configured to trigger thedetection of each car at the same location of the track as it travelswithin view of the camera. A video trip box defining a main zone aroundeach available seat of the ride car is established. In addition, one ormore sub-zones may be established defining the boundaries of the car,the position of a restraint device, a minimum rider size, and so forth.Each trip box or zone is analyzed to determine whether a rider ispresent in that seat. If so, each sub-zone is analyzed to determinewhether an exception condition exists which demands attention or aresponse. For instance, if no restraint device is detected in therestraint sub-zone, an unsecured rider exception is raised. If a portionof an individual is detected both within a main zone and outside of thecar boundary zone, an unsafe rider exception is raised.

In another embodiment, an aspect ratio analysis or zone morphologyanalysis is performed on each detected rider. The shape of each detectedrider is compared to one or more predetermined characteristics toascertain whether the rider is improperly positioned, e.g., standing,sitting on another's lap, kneeling, legs crossed over the legs ofanother, slouched under a restraint bar, etc. An aspect ratio of abounding box established around a rider is determined. Additionally oralternatively, an absolute height and width of a rider may beestablished, and/or a weighted centroid of a rider may be determined.The measured aspect ratio, absolute height, absolute width, and weightedcentroid values are compared with predetermined ranges of aspect ratio,absolute height, absolute width, and weighted centroid to determinewhether the rider falls within acceptable limits. In some embodiments, asimple rules-based algorithm may be used in order to enhance processingefficiency. In other embodiments, a lookup table, or a formula may beutilized. In some embodiments, parameters from two or more frames ofvideo may be averaged to reduce false positives and increase systemconfidence and accuracy.

In still another embodiment, a chromatic analysis may be performed oneach rider to detect and compare colors associated with known visualelements of a ride and its surroundings (color of seats, color ofrestraint devices, walkways, walls, etc.) and with the rider and/or therider's clothing. For example, color schemes associated with rideequipment (red pin in black seat buckle, bottom of safety bar mayinclude bright color, alternating yellow/black stripes, etc.) may bedetected or appear in view when properly engaged or configured. If theexpected colors are not detected at the expected location, an unsecuredrider exception is flagged. The system may include analytics thatrecognize two people in a single seat by facial recognition, countingappendages, recognizing two different garments, etc.

In yet another embodiment, markers or coatings invisible to the humaneye may be incorporated into ride elements to facilitate recognition ofriders and rider posture, and to improve contrast between ride elements(e.g., background elements in a scene) and riders. For example,fluorescent infrared paint (e.g., coatings which are highly reflectiveto IR light) may be used on some or all of a ride, or on certain rideelements. Use of an IR light source in conjunction with a digital videoanalytics camera of the present disclosure may increase systemconfidence, response time, and enable the aesthetic design of the rideto be unencumbered by human-perceivable markings which may detract fromthe theme park experience.

In some embodiments, one or more human-readable and/or barcode labelsthat uniquely identify the ride car, and/or individual seat positionsmay be utilized. The label and/or barcode may be of sufficient size tobe readily resolvable by the analytics camera. When the frame(s) areanalyzed, information encoded in the label and/or barcode is decoded andassociated with the rider(s) and/or the ride car(s) present in theframe, e.g., as metadata. In this manner, as events are detected, therelevant ride cars and seat positions related to the events may be usedto facilitate rapid and positive identification of the ride car and/orpersons of interest. In embodiments, the ride car and/or seatidentification may be communicated to a ride control system, which mayin response bring the ride to a halt, slow the ride, activate a spottinglamp above a flagged rider's head, present a message to the riderinstructing him or her to latch the restraint device, sit down, placehands in the car, etc. Additionally or alternatively, ride car and/orseat identification may be communicated to a security system, which, inturn, may log the event, store a recorded video clip of the event.Additionally or alternatively, ride car and/or seat identificationand/or associated video or still images may be communicated to amusementpark personnel via display device and/or a mobile device, such as asmartphone or pager, to enable the appropriate personnel to quickly andeffectively respond to security and safety issues identified by thedisclosed system.

The video analytics may also detect if a person is not correctlypositioned inside the ride or slipping out of the safety bar during theride by any one of the above discussed techniques. In this instance thevideo analytics can send an error message to the ride controller tosafely stop the ride or trigger an automatic slow down and stopprocedure based on where the car is along the ride (e.g., with respectto roller coaster).

For certain rides that have restrictions as to where smaller children(or adults) of a certain size may sit, the system may be configured torecognize these individuals based on seated height and alert theoperator or suspend the ride until the person is repositioned in anotherseat in the ride. For example, a small child may be allowed on the ridewith an adult but is not permitted to sit in the front car (or the frontof the car) or to one particular side (inside versus outside). Duringbusy ride times this can be a real safety concern if operators do notcatch each instance that this occurs. Once alerted, the ride operatorcan easily make these adjustments without unduly delaying the ride.

The video analytics may also be utilized to regulate or control the gapbetween ride cars, which can be a real safety concern, particularly withbusy or crowded rides. By analyzing real time images and makingautomatic or manual adjustments (e.g., the track may be equipped withdampeners or various slow down mechanisms to allow automatic or manualcontrol of the gap between cars), the pace and speed of a ride may beadjusted to safely accommodate varying crowd conditions. In theseembodiments, analytics data may be communicated to a ride control systemand/or to manual operators to adjust ride speed, frequency of departure,and the like. The analytics may also be utilized to automatically detectwhether a passenger has fallen out of a ride or gotten out on his/herown accord (behavior which is not uncommon on frightening rides). It isnot uncommon for a rider of a frightening ride (or possibly any ride) toattempt to exit the ride car after the ride has commenced. Smallchildren may particularly pose a safety concern in this area. Theanalytics and system may be designed to include a trip box feature thatis designed to surround the ride car and alert the ride operator of anunsafe condition or perform an automatic slow down and stop should aperson exit the ride prematurely.

In a typical ride all of the cameras associated with that ride may beconfigured to include one or more of the above noted analytical tools orthe video data from a camera, array of cameras or camera system may beanalyzed by a server.

With any of the aforedescribed scenarios or alerts noted herein, thesoftware may work in conjunction with a video library of images oralgorithms to trigger alerts or respond to queries. Additional images,such library images and/or user generated images, may be provided asinputs to the software and used to analyze video through the recognitionsoftware. This may all happen in real time or during post time analysis.Again queries may be entered depending upon a particular purpose and thesystem can in real time or post time analyze video for the queriedconditions.

In some instances, ride manufacturers might benefit from any of theabove discussed video analytics to provide future better designed orsafer rides.

With reference to FIG. 1, a video observation, surveillance andverification system according to an embodiment of this disclosure isshown as 100. System 100 is a network video recorder that includes theability to record video from one or more cameras 110 (e.g. analog and/orIP camera). System 110 includes one or more video cameras 110 thatconnect to a computer 120 across a connection 130. Connection 130 may bean analog connection that provides video to the computer 120, a digitalconnection that provides a network connection between the video camera110 and the computer 120, or the connection 130 may include an analogconnection and a digital connection.

System 100 may include one or more video cameras 110 wherein each videocamera 110 connects to the computer 100 and a user interface 122 toprovide a user connection to the computer 120. The one or more videocameras 110 may each connect via individual connections, may connectthrough a common network connection, or through any combination thereof.

System 100 includes at least one video analytics module 140. A videoanalytics module 140 may reside in the computer 120 and/or one or moreof the video cameras 110. Video analytics module 140 performs videoprocessing of the video. In particular, video analytics module 140performs one or more algorithms to generate non-video data from video.Non-video data includes non-video frame data that describes content ofindividual frames such as, for example, objects identified in a frame,one or more properties of objects identified in a frame and one or moreproperties related to a pre-defined portions of a frame. Non-video datamay also include non-video temporal data that describes temporal contentbetween two or more frames. Non-video temporal data may be generatedfrom video and/or the non-video frame data. Non-video temporal dataincludes temporal data such as temporal properties of an objectidentified in two or more frame and a temporal property of one or morepre-defined portions of two or more frames. Non-video frame data mayinclude a count of objects identified (e.g., objects may include peopleand/or any portion thereof, inanimate objects, animals, vehicles or auser defined and/or developed object) and one or more object properties(e.g., position of an object, position of any portion of an object,dimensional properties of an object, dimensional properties of portionsand/or identified features of an object) and relationship properties(e.g., a first object position with respect to a second object), or anyother object that may be identified in a frame. Objects may beidentified as objects that appear in video or objects that have beenremoved from video.

Video analytics module 140 positioned in a camera 110 converts video tovideo data and non-video data from the camera 110 and provides the videodata and the non-video data to the computer 120 over a network. As such,the system 100 distributes the video processing to the edge of thenetwork thereby minimizing the amount of processing required to beperformed by the computer 120.

Computer 120 includes computer-readable medium including software formonitoring user behavior, which software, when executed by a computer120, causes the computer 120 to perform operations. User interface 122provides an interface to the computer 120. User interface 122 mayconnect directly to the computer 120 or connect indirectly to thecomputer 120 through a user network.

A user behavior is defined by an action, an inaction, a movement, aplurality of event occurrences, a temporal event, an externallygenerated event or any combination thereof. A particular user behavioris defined and provided to the computer 120.

An action may include moving a safety bar, repositioning a safety bar,moving a hand, arm, leg, foot and/or body out of a designated area.Other examples are discussed above.

Inaction may include a ride operator failing to engage a safetymechanism or failing to reposition a small child from an unauthorizedseat. Inaction may also include failing to walk to a particulardesignated safe area for a ride operator or failure to perform aparticular task. An example of an inaction is a ride operator not beingstationed at an assigned area, e.g., height control area or in an areadesignated for viewing safety features, e.g., that pins are engaged orbars are secured.

As various changes could be made in the above constructions withoutdeparting from the scope of the disclosure, it is intended that allmatter contained in the above description shall be interpreted asillustrative and not in a limiting sense. It will be seen that severalobjects of the disclosure are achieved and other advantageous resultsattained, as defined by the scope of the following claims.

What is claimed is:
 1. A video analytics module comprising: a processor;and a memory storing instructions that, when executed by the processor,cause the processor to: store, in the memory, user behavior type dataindicating a plurality of types of user behaviors and rule dataindicating a plurality of predetermined rules associated with theplurality of types of user behaviors, and entertainment device dataindicating a plurality of types of entertainment devices, wherein eachof the plurality of predetermined rules is associated with a respectivetype of entertainment device of the plurality of types of entertainmentdevices; receive video camera data from a video camera; determine a userbehavior based on the received video camera data; compare the determineduser behavior to the plurality of types of user behaviors indicated bythe stored user behavior type data; transmit a notification based on aresult of the comparison and the stored plurality of rules indicated bythe rule data; analyze the video camera data to determine a type ofentertainment device; and choose a rule from the plurality ofpredetermined rules associated with the plurality of types of userbehaviors based on the determined type of entertainment device, whereinthe determined user behavior is compared to the chosen rule.
 2. Thevideo analytics module according to claim 1, wherein the memory furtherstores instructions that, when executed by the processor, cause theprocessor to: store, in the memory, safety position data indicating asafety device position rule; analyze the video camera data to determinea safety device position of a safety device; compare the safety deviceposition to the safety device position rule; and transmit a notificationbased on a result of the comparison.
 3. The video analytics moduleaccording to claim 2, wherein the memory further stores instructionsthat, when executed by the processor, cause the processor to: associatethe safety device position rule with a type of entertainment device;analyze the video camera data to determine the type of entertainmentdevice; and choose the safety device position rule based on the type ofentertainment device.
 4. The video analytics module according to claim3, wherein the safety device position rule is chosen based on a color ofthe safety device.
 5. The video analytics module according to claim 4,wherein the safety device includes a fluorescent infra-red pigment. 6.The video analytics module according to claim 5, wherein the videocamera is configured to capture infra-red images of the safety device.7. The video analytics module according to claim 3, wherein the memoryfurther stores instructions that, when executed by the processor, causethe processor to cease operation of the entertainment device if it isdetermined that the safety device position violates the safety deviceposition rule.
 8. The video analytics module according to claim 3,wherein the memory further stores instructions that, when executed bythe processor, cause the processor to activate a visual indicator if itis determined that the safety device position violates the safety deviceposition rule.
 9. The video analytics module according to claim 1,wherein the user behavior rule includes at least one of an aspect ratio,an absolute height, absolute width, or a weighted centroid.
 10. Thevideo analytics module according to claim 1, wherein the memory furtherstores instructions that, when executed by the processor, cause theprocessor to receive position data indicating a position of theentertainment device.
 11. The video analytics module according to claim1, wherein the received video camera data includes video data andnon-video data.
 12. An entertainment device safety method, comprising:storing user behavior type data indicating a plurality of types of userbehaviors and rule data indicating a plurality of predetermined rulesassociated with the plurality of types of user behaviors, andentertainment device data indicating a plurality of types ofentertainment devices, wherein each of the plurality of predeterminedrules is associated with a respective type of entertainment device ofthe plurality of types of entertainment devices; receiving video cameradata from a video camera; determining a user behavior based on thereceived video camera data; comparing the determined user behavior tothe plurality of types of user behaviors indicated by the stored userbehavior type data; transmitting a notification based on a result of thecomparison and the stored plurality of rules indicated by the rule data;analyzing the video camera data to determine a type of entertainmentdevice; and choosing a rule from the plurality of predetermined rulesassociated with the plurality of types of user behaviors based on thedetermined type of entertainment device, wherein the determined userbehavior is compared to the chosen rule.
 13. The entertainment devicesafety method according to claim 12, further comprising: storing safetyposition data indicating a safety device position rule; analyzing thevideo camera data to determine a safety device position of a safetydevice; comparing the safety device position to the safety deviceposition rule; and transmitting a notification based on a result of thecomparison.
 14. The entertainment device safety method according toclaim 13, further comprising: associating the safety device positionrule with a type of entertainment device; analyzing the video cameradata to determine the type of entertainment device; and choosing thesafety device position rule based on the type of entertainment device.15. The entertainment device safety method according to claim 14,wherein the safety device position rule is chosen based on a color ofthe safety device.
 16. The entertainment device safety method accordingto claim 14, further comprising causing the processor to cease operationof the entertainment device if it is determined that the safety deviceposition violates the safety device position rule.